计算机与现代化 ›› 2013, Vol. 1 ›› Issue (3): 71-73.doi:

• 算法分析与设计 • 上一篇    下一篇

叶面积指数遥感反演算法研究

周 洋1,2,米晓飞2,叶李灶1   

  1. 1.福建师范大学,福建福州650224; 2.中国科学研究院遥感应用研究所,北京100000
  • 收稿日期:2012-10-09 修回日期:1900-01-01 出版日期:2013-04-03 发布日期:2013-04-03

Research on Leaf Area Index Remote Sensing Inversion Algorithms

ZHOU Yang1,2, MI Xiao-fei2, YE Li-zao1   

  1. 1. Fujian Normal University, Fuzhou 650224, China; 2. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100000, China
  • Received:2012-10-09 Revised:1900-01-01 Online:2013-04-03 Published:2013-04-03

摘要: 叶面积指数是确定陆表生态系统物质和能量交换大小的重要结构参数之一。本文基于NDVI、RVI的反演模型,结合GDAL影像库和C+〖KG-*3〗+语言设计实现相关算法,形成从影像数据到叶面积指数图的处理流程,提高了影像的利用率。经预处理的Hyperion数据测试,算法运行稳定且计算结果精确,为植物长势监测、粮食产量预测提供可靠数据源。

关键词: 叶面积指数, GDAL, C+〖KG-*3〗+, C#, 影像处理

Abstract: Leaf area index is one of the important structural parameters to ensure land surface ecosystem substances and the size of energy exchange, this algorithm is designed on NDVI, RVI inversion model, combine the GDAL image library and C++ language to realize. It has achieved the operational flow from image data to leaf area index map, which improve the utilization rate of image data. The algorithm runs stable and accurate by the test of pretreatment Hyperion data, and provides reliable data for plant growth monitoring, forecast the grain production.

Key words: leaf area index, GDAL, C++, C#, image processing